Author:
Rajiv R. Asha,Bhardwaj Shambhu,Singh Vikram,Kolluru Dakshinamurthy V.,Sharma Mohit Kumar,Ashwini B.
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials
Reference20 articles.
1. Cao, Y., Lien, S.Y., Liang, Y.C., Chen, K.C., Shen, X.: User access control in open radio access networks: A federated deep reinforcement learning approach. IEEE Trans. Wirel. Commun. 21(6), 3721–3736 (2021a)
2. Cao, Y., Lien, S.Y., Liang, Y.C., Chen, K.C.: Federated deep reinforcement learning for user access control in open radio access networks. In: ICC 2021-IEEE International Conference on Communications, IEEE, pp. 1–6 (2021)
3. Chang, Q., Jiang, Y., Zheng, F.C., Bennis, M., You, X.: Cooperative edge caching via multi agent reinforcement learning in fog radio access networks. In: ICC 2022-IEEE International Conference on Communications, IEEE, pp. 3641–3646 (2022)
4. Chen, X., Zhang, H., Wu, C., Mao, S., Ji, Y., Bennis, M.: Optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning. IEEE Internet Things J. 6(3), 4005–4018 (2018)
5. Deka, K., Sharma, S.: Hybrid NOMA for future radio access: design, potentials and limitations. Wireless Personal Communications, pp. 1–16 (2022)
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